# Carga de paquetes
library(dplyr)
library(sf)
library(DT)
library(plotly)
library(leaflet)
library(raster)
library(spData)
library(lessR)
# Carga de datos
Primates<-
st_read("https://raw.githubusercontent.com/gf0604-procesamientodatosgeograficos/2021i-datos/main/gbif/primates-cr-registros.csv",
options = c(
"X_POSSIBLE_NAMES=decimalLongitude",
"Y_POSSIBLE_NAMES=decimalLatitude"
),
quiet = TRUE
)
# Asignación del sistema de coordenadas
st_crs(Primates)<-4326
# Capa geoespacial de cantones
cantones <-
st_read(
"https://raw.githubusercontent.com/gf0604-procesamientodatosgeograficos/2021i-datos/main/ign/delimitacion-territorial-administrativa/cr_cantones_simp_wgs84.geojson",
quiet = TRUE
)
# Cruce espacial con la tabla de cantones, para obtener el nombre del cantón
Primates <-
Primates %>%
st_join (cantones["canton"])
Primates %>%
st_drop_geometry() %>%
dplyr::select(family, species, stateProvince, canton, eventDate) %>%
datatable(
colnames = c("Familia", "Especies", "Provincia", "Cantón", "Fecha"),
options = list(
searchHighlight = TRUE,
pageLength = 5,
language = list(url = '//cdn.datatables.net/plug-ins/1.10.11/i18n/Spanish.json')
)
)
Grafi_pie <- data.frame("categorie"=rownames(Primates), Primates)
datos <- Grafi_pie[,c('categorie', 'species', 'individualCount')]
plot_ly(datos, labels = ~species,
values = ~individualCount,
type = 'pie'
)%>%
layout(title ="Registro de especies de primates y su porcentaje",
xaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE),
yaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE),
list(pieLength = 5,
language = list(url = '//cdn.datatables.net/plug-ins/1.10.11/i18n/Spanish.json')))
Creación de capas
#
Mo_congo<-
Primates%>%
filter(species == "Alouatta palliata")